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In our previous article (How to Scale up Ethereum Blockchain Applications), we covered how to scale up Ethereum blockchain applications.
In this article, we review different scaling solutions for Ethereum blockchain applications.
Ethereum scaling solutions
Ethereum scalability solution is one of most active topics in the Ethereum community. The following are a few areas of concern the community is trying to tackle:
- Transaction processing and block creation time with PoW—how fast can the miners process all transactions and create a new block through mining?
- Transaction finality – how soon can the decentralized network reach consensus that a transaction has happened and can’t be reverted? Currently it takes about six blocks in Bitcoin and 3-4 minutes in Ethereum for the network to consider a block is finalized in the main chain.
Solutions being implemented or proposed, fall into three categories: on-chain solution, off- chain solution, and consensus mechanism protocols. There are some obvious or theoretical ones, like increasing block size or slicing one blockchain into many independent altcoin chains. Due to the nature of peer to peer, a traditional horizontal scaling approach may not work.
Specific to the Ethereum network, some consideration was also given to stateful or stateless smart contracts contributing to scalability issues. We will go over high-level concepts of all those solutions, and then delve deeper into some of the promising ones.
This is similar to the vertical scaling approach. Some of the altcoins, like Bitcoin Cash, Ethereum Core, and so on, are implementing a larger block size to gain overall transaction performance. The theory behind this approach is that since PoW mining is the main bottleneck in the entire process, by increasing the block size we can have more transactions processed per mining. It may take a little bit longer to create a directed acyclic graph (DAG) for stash-based mining, but the average time to complete the mining may not get any worse, since most of the Ethereum clients cache the DAG anyway.
The following diagram illustrates how this technique works:
However, like vertical scaling, in general, this solution demands that network nodes have better computing capacity in order to process large sized blocks. This may lead to a scenario where a network is concentrated into a few rich hands and, thus, may ultimately compromise decentralization and security, the main tenets of the blockchain.
Another solution is not to have one gigantic blockchain, but to have many smaller blockchains and altcoins. This may eventually be the case, since many vertical industries are creating or plan to create industry-specific chains. This will reduce user activity on each individual blockchain and, thus, should allow for a more scalable ecosystem.
The following diagram illustrates how this technique works:
However, there are a few issues with this option. One is security concerns. It is a common belief that the network is more secure if more network nodes participate in the transaction processing in the blockchain. With wider distribution of altcoin chains, fewer nodes will operate on any given blockchain. This may make the blockchain less secure, since a smaller altcoin network may be more vulnerable to network attacks. Let us say, we have about 10,000 nodes on the larger network, it will require at least 5,001 nodes (or called 51%) to be compromised to launch an attack on the network. If we slice 10,000 nodes into 50 smaller chains, each chain comprises 200 nodes, and it only requires 101 nodes to take down any smaller chain, which is what we call a 1% attack problem.
Another issue is cross chain integration. Although there are some solutions for handling cross blockchain integration, the overall complexity of integrating smaller chains and altcoins will increase drastically.
On-chain solutions, sometimes also called layer 1 solutions, are to look for solutions to address scalability and performance issues at the base layer of the Ethereum blockchain network. One such solution is sharding. Sharding is not a new concept as traditional RDBMS and new big data platforms have been using sharding as a way to improve scalability and performance for many years.
With the Ethereum network, the purpose of sharding is to group the network nodes, the blockchain, and global states into different shards, and each shard will reach a consensus on the shard-wide transaction state among those nodes within the group. At the conceptual level, this may not be much different from Plasma, the layer 2 side-chain approach, but the technical difficulty, implications, and network efforts are quite different. We will go into detail about sharding in the Ethereum sharding and Casperarticle.
Another layer 1 or on-chain solution is the shift to a Proof-of-Stake(PoS) consensus mechanism, which is one of the most active research areas addressing scalability and performance issues in Ethereum. There are many debates in terms of advantages and disadvantages of a PoW-based consensus mechanism. It is quite effective in securing the blockchain in the decentralized network, but it is also a major bottleneck in the blockchain performance.
Similar to the rationales for an on-chain solution, the Ethereum community is also actively looking for off-chain solutions, sometimes called layer 2 solutions. One is a side-chain solution with Plasma. Instead of putting all transactions in the main chain, Plasma allows anyone to create side chains and bond side chains into the global blockchain. This is similar to the lighting network solution in Bitcoin.
Another one is a state channel solution with Raiden, similar to payment channels in Bitcoin. The hypothesis behind this approach is that many interparty transactions only need to be validated by the parties involved, and there is no need to have all transactions to be validated by the entire network. We will discuss in detail how they work in the next article.
One of the Bitcoin limitations is the privacy issue. Zcash is the first and perhaps the most popular cryptocurrency to implement Zero-Knowledge Succinct Non-Interactive Argument of Knowledge, or abbreviated as ZK–SNARKs, as a means of addressing privacy issues in the public blockchain.
It maintains strong privacy by allowing the transaction to be fully encrypted on the blockchain, and encrypted transactions can still be verified as valid with ZK-SNARK proofs. Under ZK-SNARK consensus rules, one, as the prover, can let others, as the verifiers, know that it possesses certain knowledge without revealing the specific knowledge, and without any interaction between them.
Ethereum community is incorporating ZK-SNARK into the Ethereum blockchain implementation too, with an intention to use ZK-SNARK to mass-validate transactions, thus improving the Ethereum scalability dramatically.
In our next article (How to Manage Ethereum State Channel with Raiden), we discuss how to manage Ethereum state channel with Raiden.
This article is written in collaboration with Brian Wu who is a leading author of “Learn Ethereum: Build your own decentralized applications with Ethereum and smart contracts” book. He has written 7 books on blockchain development.
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